The use of multiple antennas at base stations and in terminals has gained at lot of interest in the industry as well as in standardization bodies and in international research projects. Multiple antenna techniques are currently believed to be a key technology in the (long-term) evolution of existing wireless systems and in the development of future systems. At the same time, efficient resource management in terms of multi-user scheduling and link adaptation as well as so called cross-layer optimization with the physical layer are likewise challenging, promising, and important areas.
From a multi-user resource allocation and link adaptation perspective it appears to be a key component to achieve a measure that can be used to predict the performance of different allocations with respect time-frequency-code resources, modulation, code rate and transport block length as well as different spatial configurations such as transmit weights and linear dispersion codes. An algorithm will then evaluate performance, e.g. in terms of the average expected throughput or probability of successful transmission, for different schemes and allocations and select an allocation in terms of users and corresponding modes that meets the desired targets such as, e.g., maximum throughput for non delay sensitive services or negligible error probability for a re-transmission associated with a delay sensitive service.
Performance prediction is also of interest from a system performance point-of-view. Performance models based on mapping a scalar single antenna/stream SINR to mutual information and averaging in the information domain has been considered.
Efficient resource management thus requires reasonable performance prediction and for this purpose it may be realized that adequate measurements of channel and interference conditions are required. As of today, e.g. in an evolved 3G system, a scalar valued channel quality indicator (CQI) in terms of an SINR after receiver processing or the corresponding preferred transport format which corresponds to a data rate is typically used.
Linear receive and transmit schemes, such as beam forming and linear dispersion codes with linear receivers may in principle be incorporated by adjusting the SINR calculation, but then the measurements become specific for the by the terminal assumed spatial transmit and receive processing. Thus, the terminal may determine suitable transmit weights or a selection of transmit antennas and evaluate the performance for this choice only. It is then, however, not trivial for the transmitter to evaluate a selection of a different transmit scheme which may be required when considering multi-user, multi-cell, multi-system aspects. Also, it is not obvious how to incorporate non-linear demodulation schemes, such as (approximate) maximum likelihood demodulations.